Evaluation of soil heavy metals pollution and the phytoremediation potential of copper-nickel mine tailings ponds

Heavy metal pollution in soils caused by mining has led to major environmental problems around the globe and seriously threatens the ecological environment. The assessment of heavy metal pollution and the local phytoremediation potential of contaminated sites is an important prerequisite for phytoremediation. Therefore, the purpose of this study was to understand the characteristics of heavy metal pollution around a copper-nickel mine tailings pond and screen local plant species that could be potentially suitable for phytoremediation. The results showed that Cd, Cu, Ni, and Cr in the soil around the tailings pond were at the heavy pollution level, Mn and Pb pollution was moderate, and Zn and As pollution was light; The positive matrix factorization (PMF) model results showed that the contributions made by industrial pollution to Cu and Ni were 62.5% and 66.5%, respectively, atmospheric sedimentation and agricultural pollution contributions to Cr and Cd were 44.6% and 42.8%, respectively, the traffic pollution contribution to Pb was 41.2%, and the contributions made by natural pollution sources to Mn, Zn, and As were 54.5%, 47.9%, and 40.0% respectively. The maximum accumulation values for Cu, Ni, Cr, Cd, and As in 10 plants were 53.77, 102.67, 91.10, 1.16 and 7.23 mg/kg, respectively, which exceeded the normal content of heavy metals in plants. Ammophila breviligulata Fernald had the highest comprehensive extraction coefficient (CEI) and comprehensive stability coefficient (CSI) at 0.81 and 0.83, respectively. These results indicate that the heavy metal pollution in the soil around the copper nickel mine tailings pond investigated in this study is serious and may affect the normal growth of plants. Ammophila breviligulata Fernald has a strong comprehensive remediation capacity and can be used as a remediation plant species for multiple metal compound pollution sites.

In summary, the aims of this study were (1) to explore the impact of tailings accumulation on 87 the enrichment of heavy metals in the surrounding soil, (2) clarify the sources of heavy metals in 88 soil and provide reasonable suggestions for the effective prevention and control of heavy metal 89 pollution in soil, and (3) evaluate the phytoremediation potential of native plants to provide a 90 reference basis for the phytoremediation of heavy metal contaminated soil. 91

Study area description and sample collection 93
The copper-nickel mine tailings pond was built in 1999 and is located in northern Xinjiang 94 Province and in the eastern part of Fuyun County (Fig. 1). The design level of the pond capacity is 95 grade Ⅴ and the floor area is about 1.5 × 10 5 m 2 . The slag waste is disposed of by the traditional wet 96 discharge method and the discharge volume is about 1,000 t/d. The altitude of the area ranges from 97 500-900 m and the soil types are mainly light brown calcium soil and typical brown calcium soil. 98 The area is subjected to a continental cold temperate climate. It is dry and windy in spring, but cold 99 in winter. There are also large temperature differences between day and night. The annual average 100 temperature is 3.0℃, the annual precipitation is 186.4 mm, the annual evaporation is 1,829.7 mm, 101 the annual extreme maximum temperature is 42.2℃, and the extreme minimum temperature is -

Sample processing and determination 115
The plant samples were first washed with tap water and then three times with deionized water. 116 They were placed in an oven at 105℃ for 20 minutes, dried at 70℃ to a constant weight, ground 117 with a grinder to pass through a 100 mesh nylon sieve, and bagged. Then, 0.2 g subsamples of the 118 plants were weighed out, placed in a microwave digester, and digested in an HNO3-H2O2 digestion 119 system (HNO3:H2O2 = 5:1, volume ratio) until the liquid clarified. The soil samples were dried after 120 removing impurities, such as stones and animal and plant residues. These samples were then ground 121 with agate mortar through a 200 mesh nylon sieve, and bagged until needed. Then, 0.1 g subsamples 122 of the soil were digested in a microwave digester under a HNO3-HF-HClO4 digestion system 123 (HNO3:HF:HClO4 = 3:1:1, volume ratio) until the liquid clarified. The experiment was verified 124 using the blank control method, the double parallel sample method, and the standard addition 125 recovery method to ensure the accuracy of the experimental and determination processes. The 126 supernatants from the subsamples were removed and the contents of eight heavy metals (Cr, Ni, Cu, 127 Zn, Cd, Pb, Mn, As) were determined by inductively coupled plasma mass spectrometry (ICP-MS). 128

Single factor pollution index method 130
The single factor pollution index (Pi) is a common method used to evaluate the degree to which 131 a soil has been polluted with heavy metals ( were divided into five grades: Pi ≤ 0.7, safe; 0.7 < Pi ≤ 1.0, warning; 1 < Pi ≤ 2, slight pollution; 2 139 < Pi ≤ 3, moderate pollution; and Pi > 3, heavy pollution. 140

Nemerow comprehensive pollution index method 141
The Nemerow comprehensive pollution index is used to calculate the comprehensive pollution 142 where Pcom is the composite contamination index, Pave is the average value of the single-factor index, 147 and Pmax is the maximum value of the single-factor index. The evaluation results were divided into 148 five grades: Pcom ≤ 0.7, safe; 0.7 < Pcom ≤ 1.0, warning; 1 < Pcom ≤ 2, light pollution; 2 < Pcom ≤ 3, 149 moderate pollution; and Pcom > 3, heavy pollution.
where represents the ith heavy metal element; is the enrichment coefficient of plants for 158 the ℎ heavy metal, which is a parameter that is used to evaluate the ability of plant stems and 159 leaves to extract heavy metals from soil; is the stability coefficient of plants for the ℎ heavy 160 metal and is a parameter used to evaluate the ability of plant roots to stabilize heavy metals; ℎ 161 is the content of the ℎ heavy metal in the aboveground part of the plant; is the content of 162 the ℎ heavy metal in the underground part of the plant; and is the content of the ℎ heavy 163 metal in the plant growth matrix. 164

Comprehensive extraction index for plants 165
The comprehensive extraction index (CEI) for plants is based on fuzzy synthesis and can be 166 comprehensive extraction potential of plants is divided into three grades, poor (CEI ≤ 0.4), good 176 (0.4 < CEI < 0.7), and excellent (CEI ≥ 0.7). 177

Plant comprehensive stability index 178
The plant comprehensive stability index (CSI) is based on fuzzy synthesis and can be used to 179 evaluate the plant root comprehensive stability potential for various heavy metals under multiple 180 heavy metal combined pollution conditions. The calculation formula is as follows: 181 where is the comprehensive stability index for a plant; is the total number of heavy metals 184

Statistical characteristics of soil heavy metal content 196
According to the descriptive statistical analysis (Table 2) respectively, which showed that the variation indexes were relatively weak. The variation indexes 207 7 for Zn and Mn were 11.87% and 9.38%, respectively, which are less than 25% and shows that the 208 variation was low and that they are less affected by external conditions. 209 210

Evaluation of heavy metal pollution in soil 215
The pollution caused by different heavy metal elements in the soil was evaluated using Formula 216 (1). The results (Fig. 2) show that the single factor pollution indexes for heavy metal elements Cd, 217 Cu, Ni, Cr, Mn, Pb, Zn, and As were between 22.5-108.5, 11.5-62.0, 14.8-107.6, 1.7-6.1, 1.9-2.6, 218 0.9-3.6, 1.4-2.2, and 0.5-2.2, respectively. Among them, the average single factor pollution indexes 219 for Cd, Cu, Ni, and Cr were 53.2, 27.7, 43.9, and 3.5, respectively, which were greater than 3 and 220 meant that they reached the heavy pollution grade; the single factor pollution index mean values for 221 Mn and Pb were 2.3 and 2.1, respectively, which were at the moderate pollution level; and the single 222 factor pollution index mean values for Zn and As were 1.7 and 1.2, respectively, which were at the 223 light pollution level. The Nemerow comprehensive pollution index results, calculated using 224 Formula (2) (Fig. 2), showed that the Nemerow pollution indexes for all sample points ranged from 225 25.0 to 79.0, with an average of 43.9, which was at the heavy pollution level. In general, the soil 226 was heavily polluted with metals and remediation measures were urgently needed.  (Fig. 3). Among them, the correlations between Ni and Cu, Zn, Pb, Cr and Cd, Pb, Cu, and 235 Zn, and Pb, Cd, and Pb reached a very significant level (P < 0.01). These results showed that there 236 were strong correlations among some of the heavy metals. The correlations between Ni and Cd, and 237 Cu and Cd, Zn, and Pb reached significant levels (P < 0.05). The analysis results for the sources of 238 heavy metals in the soil obtained from the study area using the PMF model (Fig. 3)  seen in the study soil. Therefore, Factor 1 came from composite pollution sources, including 249 atmospheric deposition and agricultural pollution sources. Factor 2 contributed most to Cu and Ni 250 levels at 62.5% and 66.5%, respectively. The correlation analysis showed that the correlation 251 9 between Cu and Ni was high at 0.88, indicating that Cu and Ni had the same pollution source. The 252 sampling points were located near the copper nickel mining, smelting, and tailings pond, which 253 suggests that Factor 2 is based on industrial pollution sources. Factor 3 contributed 54.5%, 47.9%, 254 and 40.0% to Mn, As, and Zn, respectively. Table 1 shows that the variation indexes for Mn, As, 255 and Zn were low; and the single factor pollution evaluation results (Fig. 2) showed that Mn was 256 moderately polluting, whereas As and Zn were slightly polluting. These results consistently showed 257 that Mn, As, and Zn were less disturbed by human factors. Previous studies have shown that Mn 258 mainly came from soil parent materials (Luo et al., 2022;Lv, 2019;Lv et al., 2015). Therefore, 259 Factor 3 was based on natural sources. Factor 4 made the greatest contribution toward Pb levels at (aboveground and underground parts), except for A. breviligulata, did not exceed the maximum 293 normal range (normal range for As: 1-1.5 mg/kg), and the Mn, Zn, and Pb contents in all plants 294 (aboveground and underground parts) were within the normal range (normal range for Mn: 30-300 295 mg/kg, normal range for Zn: 25-250 mg/kg, and normal range for Pb: 5-10 mg/kg). 296

Heavy metal absorption characteristics of plants 297
The biological accumulation factor (BAF) shows the ability of plant stems and leaves to 298 accumulate heavy metals, which means that it reflects the ability of plants to remove heavy metals 299 from soil. Table 3 shows that there were obvious differences in the accumulation capacity of plants Cr, P. aviculare has a strong ability to extract Zn, S. ruthenica has a strong ability to extract Cd, and 306 A. breviligulata shows a strong extraction ability for Mn, Ni, Cu, As, and Pb. 307 Plant stabilization is the use of plant roots to absorb and accumulate toxic metals in soil, thereby 308 reducing the bioavailability and migration of heavy metals in soil (Flathman et al., 1998). The 309 biological concentration factor (BCF) can reflect the ability of plants to stabilize heavy metals in 310 soil. Table 4

Comprehensive evaluation of phytoremediation potential 332
The plant comprehensive extraction index and plant comprehensive stability index results, 333 calculated based on Fuzzy evaluation (Fig. 5), showed that among the 10 plants investigated, the 334 plant comprehensive extraction indexes for P. australis, L. sinense, S. salsula, H. arachnoideus, K. 335 centauroides, P. harmala, and S. ruthenica were 0.04, 0.05, 0.14, 0.23, 0.25, 0.26, and 0.30, 336 respectively, which were less than 0.4, which meant that their comprehensive removal potentials for 337 heavy metals were poor. The plant comprehensive extraction index for A. patens was 0.52, which 338 meant that its comprehensive removal potential for heavy metals was good; and the plant 339 comprehensive extraction index for A. breviligulata was 0.83, which means that its comprehensive 340 removal potential level for heavy metals was excellent, indicating that it had a strong comprehensive 341 removal ability for heavy metals. The plant comprehensive stability indexes for P. australis, L. 342 sinense, S. salsula, A. patens, K. centauroides, P. aviculare, and H. arachnoideus were smaller at 343 0.07, 0.07, 0.08, 0.28, 0.29, 0.31, and 0.34, respectively, which are all less than 0.4. Therefore, their 344 potential stability indexes for heavy metals are poor, indicating that their comprehensive ability to 345 stabilize heavy metals is weak. The plant comprehensive stability indexes for S. ruthenica and P. 346 harmala were 0.53 and 0.60 respectively, which meant that their potential stability grades for heavy 347 metals were good. The plant comprehensive stability index for A. breviligulata was 0.81, which 348 meant that its stability potential index for heavy metals was excellent, indicating that it had strong 349 comprehensive ability to stabilize heavy metals. Therefore, A. breviligulata had greater remediation 350 potential for heavy metals in soil than the other plants. there is strong evaporation and erosion (wind erosion, hydraulic erosion, and freeze-thaw erosion). 373 Therefore, there may be a potential risk of heavy metal diffusion in the tailings pond. The evaluation 374 results for heavy metals in the soil around the copper-nickel tailings pond in this study showed that 375 Cd, Cu, Ni, and Cr were at the heavy pollution level, Mn and Pb were at the moderate pollution 376 level, and Zn and As were at the light pollution level. The source analysis using the PMF model 377 showed that pollution by Cu, Ni, Cr, and Cd was closely related to industrial activities, such as 378 mining, ore smelting, and tailings accumulation. Li et al. (2022) found that there were many kinds 379 of heavy metal pollution in the soil around a copper nickel mine tailings pond, among which Cu, 380 Ni, and Cr were the main environmental pollutants derived from tailings. Their results were similar 381 to the results obtained from this study. Liang et al. (2017) collected water, soil, rice, and vegetable 382 samples in an area near a tailings pond and found that these samples were contaminated with heavy 383 metals and posed potential health risks to nearby residents. Therefore, the diffusion of heavy metals 384 in tailings ponds will cause serious pollution to the environment and pose a serious threat to human 385 life and health. 386 Phytoremediation uses the accumulation of elements by plant stems, leaves, and roots to 387 remove and stabilize heavy metals in soil (Fig. 6). Furthermore, the plant canopy formed after 388 phytoremediation can reduce the near surface wind speed and the diffusion of fine particle pollutants, 389 while the underground root network can prevent rainfall erosion and leaching, and provide a suitable fuzzy comprehensive evaluation to evaluate the comprehensive heavy metal extraction potential of 403 woody plants growing on heavy metal contaminated sites and found that B. papyrifera could extract 404 many kinds of heavy metals at the same time. In terms of extraction potentials for single heavy 405 metals, this study found that A. patens had a strong ability to extract Cr; P. aviculare had a strong 406 Zn extraction ability; S. ruthenica had a strong Cd extraction ability; A. breviligulata had strong Mn, 407 Ni, Cu, As, and Pb extraction abilities. In terms of single heavy metal extraction and stabilization 408 abilities, this study found that S. ruthenica had a strong ability to stabilize Cr; P. harmala had a 409 strong ability to stabilize Ni, Cu, and Cd; and A. breviligulata had a strong ability to stabilize Mn, 410 Zn, As, and Pb. The evaluation results for plant heavy metal comprehensive extraction/stabilization 411 potential based on fuzzy mathematics showed that the plant comprehensive extraction and plant 412 comprehensive stability indexes for A. breviligulata were the highest, indicating that A. breviligulata 413 had better heavy metal removal and stabilization effects than the other native plants. Therefore, A. 414 breviligulata can be selected as the preferred species for heavy metal pollution remediation in the 415 study area. 416

Conclusion 418
The results showed that there was obvious compound heavy metal pollution in the soil around 419 the copper-nickel tailings reservoir area. Among them, the heavy metal elements Cd, Cu, Ni, and 420